AI Glossary
LLM (Large Language Model)
An artificial intelligence model trained on large volumes of text that can understand and generate natural language with high quality.
LLMs are the technology behind ChatGPT, Claude, Gemini and other AI assistants. Understanding what they are and their limitations is key to using them wisely in a business.
Main models (2026)
- Claude (Anthropic): the one we use most at Syncra Labs — excellent at reasoning and instruction following
- GPT-4 (OpenAI): the most well-known, good at general tasks
- Gemini (Google): integrated with the Google ecosystem
- Llama (Meta): open-source, ideal for self-hosting
Limitations to consider
- Hallucinations: they can make up information. Always verify critical data
- Context window: they have a limit to how much text they can process at once
- Cost: intensive API use can be significant
- Private data: cloud models process your data on external servers
How we use them at Syncra Labs
As tools within broader systems: agents, RAG, automations. Never as a final product without human oversight on critical decisions.
Related services
Related terms
RAG (Retrieval-Augmented Generation)
Technique that combines search in a proprietary knowledge base with AI text generation, enabling accurate responses based on your data.
AI Agent
An AI system that can plan, execute actions, and use tools autonomously to complete complex tasks.
Prompt Engineering
The discipline of designing precise instructions for AI models that maximize the quality and relevance of responses.
Fine-tuning
Process of retraining an AI model with your company's specific data so it specializes in your domain or tone.
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